Smooth 2D manifold extraction from 3D image stack

Three-dimensional fluorescence microscopy followed by image processing is routinely used to study biological objects at various scales such as cells and tissue. However, maximum intensity projection, the most broadly used rendering tool, extracts a discontinuous layer of voxels, obliviously creating important artifacts and possibly misleading interpretation.

Here we propose smooth manifold extraction, an algorithm that produces a continuous focused 2D extraction from a 3D volume, hence preserving local spatial relationships. We demonstrate the usefulness of our approach by applying it to various biological applications using confocal and wide-field microscopy 3D image stacks.

We provide a parameter-free ImageJ/Fiji plugin that allows 2D visualization and interpretation of 3D image stacks with maximum accuracy. Maximum Intensity Projection is a common tool to represent 3D biological imaging data in a 2D space, but it creates artefacts. Here the authors develop Smooth Manifold Extraction, an ImageJ/Fiji plugin, to preserve local spatial relationships when extracting the content of a 3D volume to a 2D space.